def __call__(self, corpus_name, subc_name, subchash, query, samplesize):
corpus_manager = CorpusManager()
corpus_obj = corpus_manager.get_Corpus(corpus_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
pidfile = self._create_pid_file()
cachefile, stored_pidfile = cache_map.add_to_map(subchash, query, 0, pidfile)
return dict(cachefile=cachefile, pidfile=pidfile, stored_pidfile=stored_pidfile)
def __call__(self, initial_args, subc_dir, corpus_name, subc_name,
subchash, query, samplesize):
"""
initial_args -- a dict(cachefile=..., pidfile=..., stored_pidfile=...)
subc_dir -- a directory where user's subcorpora are stored
corpus -- a corpus identifier
subc_name -- subcorpus name (should be None if not present)
subchash -- an identifier of current subcorpus (None if no subcorpus is in use)
query -- a tuple/list containing current query
samplesize -- row limit
"""
sleeptime = None
try:
corpus_manager = CorpusManager(subcpath=(subc_dir, ))
corpus_obj = corpus_manager.get_Corpus(corpus_name, subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
if not initial_args.get('stored_pidfile'):
# The conc object bellow is asynchronous; i.e. you obtain it immediately but it may
# not be ready yet (this is checked by the 'finished()' method).
conc = self.compute_conc(corpus_obj, query, samplesize)
sleeptime = 0.1
time.sleep(sleeptime)
conc.save(initial_args['cachefile'], False, True,
False) # partial
while not conc.finished():
# TODO it looks like append=True does not work with Manatee 2.121.1 properly
tmp_cachefile = initial_args['cachefile'] + '.tmp'
conc.save(tmp_cachefile, False, True, False)
os.rename(tmp_cachefile, initial_args['cachefile'])
time.sleep(sleeptime)
sleeptime += 0.1
sizes = self.get_cached_conc_sizes(
corpus_obj, query, initial_args['cachefile'])
self._update_pidfile(initial_args['pidfile'],
last_check=int(time.time()),
curr_wait=sleeptime,
finished=sizes['finished'],
concsize=sizes['concsize'],
fullsize=sizes['fullsize'],
relconcsize=sizes['relconcsize'])
tmp_cachefile = initial_args['cachefile'] + '.tmp'
conc.save(tmp_cachefile) # whole
os.rename(tmp_cachefile, initial_args['cachefile'])
# update size in map file
cache_map.add_to_map(subchash, query, conc.size())
os.remove(initial_args['pidfile'])
except Exception as e:
# Please note that there is no need to clean any mess (pidfile of failed calculation,
# unfinished cached concordance etc.) here as this is performed by _get_cached_conc()
# function in case it detects a problem.
import traceback
logging.getLogger(__name__).error(
'Background calculation error: %s' % e)
logging.getLogger(__name__).error(''.join(
traceback.format_exception(*sys.exc_info())))
self._update_pidfile(initial_args['pidfile'],
last_check=int(time.time()),
curr_wait=sleeptime,
error=str(e))
def require_existing_conc(corp: AbstractKCorpus,
q: Union[Tuple[str, ...], List[str]]) -> PyConc:
"""
Load a cached concordance based on a provided corpus and query.
If nothing is found, ConcNotFoundException is thrown.
"""
corpus_manager = CorpusManager(subcpath=[])
cache_map = plugins.runtime.CONC_CACHE.instance.get_mapping(corp)
subchash = getattr(corp, 'subchash', None)
status = cache_map.get_calc_status(subchash, q)
if status is None:
raise ConcNotFoundException('Concordance not found: {}'.format(
', '.join(q)))
if status.finished and status.readable:
mcorp = corp
for qq in reversed(q): # find the right main corp, if aligned
if qq.startswith('x-'):
mcorp = corpus_manager.get_corpus(qq[2:])
break
try:
return PyConc(mcorp, 'l', status.cachefile, orig_corp=corp)
except manatee.FileAccessError as ex:
raise ConcNotFoundException(ex)
raise BrokenConcordanceException(
'Concordance broken. File: {}, error: {}'.format(
status.cachefile, status.error))
def __init__(self, task_id, cache_factory, subc_dirs, corpus_name,
subc_name: str, conc_dir: str):
super().__init__(task_id, cache_factory)
self.corpus_manager = CorpusManager(subcpath=subc_dirs)
self.corpus_obj = self.corpus_manager.get_corpus(corpus_name,
subcname=subc_name)
setattr(self.corpus_obj, '_conc_dir', conc_dir)
self.cache_map = self._cache_factory.get_mapping(self.corpus_obj)
def __call__(self, corpus_name, subc_name, subchash, subcpaths, query, samplesize):
corpus_manager = CorpusManager(subcpath=subcpaths)
corpus_obj = corpus_manager.get_Corpus(corpus_name, subcname=subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
new_status = self.create_new_calc_status()
cachefile, prev_status = cache_map.add_to_map(subchash, query, 0, new_status)
return dict(
cachefile=cachefile,
already_running=prev_status is not None)
def __call__(self, corpus_name: str, subc_name: str, subchash: Optional[str], subcpaths: Tuple[str, ...], query: Tuple[str, ...], samplesize: int) -> Dict[str, Any]:
corpus_manager = CorpusManager(subcpath=subcpaths)
corpus_obj = corpus_manager.get_Corpus(corpus_name, subcname=subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
new_status = self.create_new_calc_status()
cachefile, prev_status = cache_map.add_to_map(subchash, query, 0, new_status)
return dict(
cachefile=cachefile,
already_running=prev_status is not None)
def __call__(self, corpus_name, subc_name, subchash, subcpath, query,
samplesize):
corpus_manager = CorpusManager(subcpath=(subcpath, ))
corpus_obj = corpus_manager.get_Corpus(corpus_name, subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
new_status = self.create_new_calc_status()
cachefile, prev_status = cache_map.add_to_map(subchash, query, 0,
new_status)
return dict(cachefile=cachefile,
already_running=prev_status is not None)
def __call__(self, corpus_name, subc_name, subchash, query, samplesize):
corpus_manager = CorpusManager()
corpus_obj = corpus_manager.get_Corpus(corpus_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
pidfile = self._create_pid_file()
cachefile, stored_pidfile = cache_map.add_to_map(
subchash, query, 0, pidfile)
return dict(cachefile=cachefile,
pidfile=pidfile,
stored_pidfile=stored_pidfile)
def __call__(self, initial_args, subc_dir, corpus_name, subc_name, subchash, query, samplesize):
"""
initial_args -- a dict(cachefile=..., pidfile=..., stored_pidfile=...)
subc_dir -- a directory where user's subcorpora are stored
corpus -- a corpus identifier
subc_name -- subcorpus name (should be None if not present)
subchash -- an identifier of current subcorpus (None if no subcorpus is in use)
query -- a tuple/list containing current query
samplesize -- row limit
"""
sleeptime = None
try:
corpus_manager = CorpusManager(subcpath=(subc_dir,))
corpus_obj = corpus_manager.get_Corpus(corpus_name, subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
if not initial_args.get('stored_pidfile'):
# The conc object bellow is asynchronous; i.e. you obtain it immediately but it may
# not be ready yet (this is checked by the 'finished()' method).
conc = self.compute_conc(corpus_obj, query, samplesize)
sleeptime = 0.1
time.sleep(sleeptime)
conc.save(initial_args['cachefile'], False, True, False) # partial
while not conc.finished():
# TODO it looks like append=True does not work with Manatee 2.121.1 properly
tmp_cachefile = initial_args['cachefile'] + '.tmp'
conc.save(tmp_cachefile, False, True, False)
os.rename(tmp_cachefile, initial_args['cachefile'])
time.sleep(sleeptime)
sleeptime += 0.1
sizes = self.get_cached_conc_sizes(corpus_obj, query, initial_args['cachefile'])
self._update_pidfile(initial_args['pidfile'], last_check=int(time.time()),
curr_wait=sleeptime, finished=sizes['finished'],
concsize=sizes['concsize'], fullsize=sizes['fullsize'],
relconcsize=sizes['relconcsize'])
tmp_cachefile = initial_args['cachefile'] + '.tmp'
conc.save(tmp_cachefile) # whole
os.rename(tmp_cachefile, initial_args['cachefile'])
# update size in map file
cache_map.add_to_map(subchash, query, conc.size())
os.remove(initial_args['pidfile'])
except Exception as e:
# Please note that there is no need to clean any mess (pidfile of failed calculation,
# unfinished cached concordance etc.) here as this is performed by _get_cached_conc()
# function in case it detects a problem.
import traceback
logging.getLogger(__name__).error('Background calculation error: %s' % e)
logging.getLogger(__name__).error(''.join(traceback.format_exception(*sys.exc_info())))
self._update_pidfile(initial_args['pidfile'], last_check=int(time.time()), curr_wait=sleeptime, error=str(e))
def __call__(self, corpus_name: str, subc_name: str,
subchash: Optional[str], subcpaths: Tuple[str, ...],
query: Tuple[str, ...], samplesize: int) -> Dict[str, Any]:
corpus_manager = CorpusManager(subcpath=subcpaths)
corpus_obj = corpus_manager.get_Corpus(corpus_name, subcname=subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
status = cache_map.get_calc_status(subchash, query)
if status is None or status.error:
status = self.create_new_calc_status()
status = cache_map.add_to_map(subchash,
query,
status,
overwrite=True)
already_running = False
else:
already_running = True
return dict(cachefile=status.cachefile,
already_running=already_running)
def _load_corp(corp_id, subc: str, user_id):
"""
Instantiate a manatee.Corpus (or manatee.SubCorpus)
instance
arguments:
corp_id -- a corpus identifier
subc -- a subcorpus identifier (None if not defined)
user_id --
"""
subc_paths = [
os.path.join(settings.get('corpora', 'users_subcpath'), 'published')
]
if user_id is not None:
subc_paths.insert(
0,
os.path.join(settings.get('corpora', 'users_subcpath'),
str(user_id)))
cm = CorpusManager(subc_paths)
return cm.get_corpus(corp_id, '', subc)
async def conc_cache_status_ws_handler(
request: web.Request) -> web.WebSocketResponse:
ws = web.WebSocketResponse()
await ws.prepare(request)
logging.debug('Client connected to conc cache status')
# wait for concordance parameters
msg = await ws.receive()
params = json.loads(msg.data)
logging.debug('Received conc parameters: %s', params)
subcpath = [
os.path.join(settings.get('corpora', 'users_subcpath'), 'published')
]
with plugins.runtime.AUTH as auth:
if not auth.is_anonymous(params['user_id']):
subcpath.insert(
0,
os.path.join(settings.get('corpora', 'users_subcpath'),
str(params['user_id'])))
cm = CorpusManager(subcpath)
corp = cm.get_corpus(corpname=params['corp_id'],
subcname=params.get('subc_path', None))
# check until finished
while not ws.closed:
try:
response = get_conc_cache_status(corp, params['conc_id'])
except Exception as e:
response = {'error': str(e), 'finished': True}
await ws.send_json(response)
if response['finished']:
await ws.close()
else:
await asyncio.sleep(CONC_CACHE_STATUS_REFRESH_PERIOD)
logging.debug('Client disconnected from conc cache status')
return ws
class ConcSyncCalculation(GeneralWorker):
"""
A worker for calculating a concordance synchronously (from Manatee API point of view)
but still in background.
Please note that the worker expects you to create required concordance cache
mapping records.
"""
def __init__(self, task_id, cache_factory, subc_dirs, corpus_name,
subc_name: str, conc_dir: str):
super().__init__(task_id, cache_factory)
self.corpus_manager = CorpusManager(subcpath=subc_dirs)
self.corpus_obj = self.corpus_manager.get_corpus(corpus_name,
subcname=subc_name)
setattr(self.corpus_obj, '_conc_dir', conc_dir)
self.cache_map = self._cache_factory.get_mapping(self.corpus_obj)
def _mark_calc_states_err(self, subchash: Optional[str], query: Tuple[str,
...],
from_idx: int, err: BaseException):
for i in range(from_idx, len(query)):
self.cache_map.update_calc_status(subchash,
query[:i + 1],
error=err,
finished=True)
def __call__(self, subchash, query: Tuple[str, ...], samplesize: int):
try:
calc_from, conc = find_cached_conc_base(self.corpus_obj,
subchash,
query,
minsize=0)
if isinstance(
conc, InitialConc
): # we have nothing, let's start with the 1st operation only
for i in range(0, len(query)):
self.cache_map.add_to_map(
subchash,
query[:i + 1],
ConcCacheStatus(task_id=self._task_id),
overwrite=True)
calc_status = self.cache_map.get_calc_status(
subchash, query[:1])
conc = self.compute_conc(self.corpus_obj, query[:1],
samplesize)
conc.sync()
conc.save(calc_status.cachefile)
os.chmod(calc_status.cachefile, 0o664)
self.cache_map.update_calc_status(subchash,
query[:1],
readable=True,
finished=True,
concsize=conc.size())
calc_from = 1
else:
for i in range(calc_from, len(query)):
self.cache_map.add_to_map(
subchash,
query[:i + 1],
ConcCacheStatus(task_id=self._task_id),
overwrite=True)
except Exception as ex:
logging.getLogger(__name__).error(ex)
manatee_err = extract_manatee_error(ex)
norm_err = manatee_err if manatee_err else ex
self._mark_calc_states_err(subchash, query, 0, norm_err)
return
# save additional concordance actions to cache (e.g. sample, aligned corpus without a query,...)
for act in range(calc_from, len(query)):
try:
command, args = query[act][0], query[act][1:]
conc.exec_command(command, args)
if command in 'gae': # user specific/volatile actions, cannot save
raise NotImplementedError(
f'Cannot run command {command} in background') # TODO
calc_status = self.cache_map.get_calc_status(
subchash, query[:act + 1])
conc.save(calc_status.cachefile)
os.chmod(calc_status.cachefile, 0o664)
self.cache_map.update_calc_status(subchash,
query[:act + 1],
readable=True,
finished=True,
concsize=conc.size())
except Exception as ex:
self._mark_calc_states_err(subchash, query, act, ex)
logging.getLogger(__name__).error(ex)
return
def __call__(self, initial_args, subc_dirs, corpus_name, subc_name,
subchash, query, samplesize):
"""
initial_args -- a dict(cachefile=..., already_running=...)
subc_dirs -- a list of directories where to look for subcorpora
corpus -- a corpus identifier
subc_name -- subcorpus name (should be None if not present)
subchash -- an identifier of current subcorpus (None if no subcorpus is in use)
query -- a tuple/list containing current query
samplesize -- row limit
"""
cache_map = None
try:
corpus_manager = CorpusManager(subcpath=subc_dirs)
corpus_obj = corpus_manager.get_corpus(corpus_name,
subcname=subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
if not initial_args['already_running']:
# The conc object bellow is asynchronous; i.e. you obtain it immediately but it may
# not be ready yet (this is checked by the 'finished()' method).
conc = self.compute_conc(corpus_obj, query, samplesize)
sleeptime = 0.1
time.sleep(sleeptime)
cachefile = initial_args['cachefile']
conc.save(cachefile, False, True) # partial
os.chmod(cachefile, 0o664)
cache_map.update_calc_status(subchash,
query,
readable=True,
task_id=self._task_id)
while not conc.finished():
conc.save(cachefile + '.tmp', False, True)
os.rename(cachefile + '.tmp', cachefile)
sizes = self.get_cached_conc_sizes(corpus_obj, query)
cache_map.update_calc_status(
subchash,
query,
finished=sizes['finished'],
concsize=sizes['concsize'],
fullsize=sizes['fullsize'],
relconcsize=sizes['relconcsize'],
arf=None,
task_id=self._task_id)
time.sleep(sleeptime)
sleeptime += 0.1
conc.save(cachefile + '.tmp') # whole
os.rename(cachefile + '.tmp', cachefile)
os.chmod(cachefile, 0o664)
sizes = self.get_cached_conc_sizes(corpus_obj, query)
cache_map.update_calc_status(
subchash,
query,
finished=sizes['finished'],
concsize=conc.size(),
fullsize=sizes['fullsize'],
relconcsize=sizes['relconcsize'],
arf=round(conc.compute_ARF(), 2)
if not corpus_obj.is_subcorpus else None,
task_id=self._task_id)
except Exception as e:
# Please note that there is no need to clean any mess (unfinished cached concordance etc.)
# here as this is performed by _get_cached_conc()
# function in case it detects a problem.
manatee_err = extract_manatee_error(e)
norm_err = manatee_err if manatee_err else e
if cache_map is not None:
cache_map.update_calc_status(subchash,
query,
finished=True,
error=norm_err)
def __call__(self, initial_args, subc_dirs, corpus_name, subc_name, subchash, query, samplesize):
"""
initial_args -- a dict(cachefile=..., already_running=...)
subc_dirs -- a list of directories where to look for subcorpora
corpus -- a corpus identifier
subc_name -- subcorpus name (should be None if not present)
subchash -- an identifier of current subcorpus (None if no subcorpus is in use)
query -- a tuple/list containing current query
samplesize -- row limit
"""
sleeptime = None
cache_map = None
try:
corpus_manager = CorpusManager(subcpath=subc_dirs)
corpus_obj = corpus_manager.get_Corpus(corpus_name, subcname=subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
if not initial_args['already_running']:
# The conc object bellow is asynchronous; i.e. you obtain it immediately but it may
# not be ready yet (this is checked by the 'finished()' method).
conc = self.compute_conc(corpus_obj, query, samplesize)
sleeptime = 0.1
time.sleep(sleeptime)
conc.save(initial_args['cachefile'], False, True, False) # partial
while not conc.finished():
# TODO it looks like append=True does not work with Manatee 2.121.1 properly
tmp_cachefile = initial_args['cachefile'] + '.tmp'
conc.save(tmp_cachefile, False, True, False)
os.rename(tmp_cachefile, initial_args['cachefile'])
time.sleep(sleeptime)
sleeptime += 0.1
sizes = self.get_cached_conc_sizes(corpus_obj, query, initial_args['cachefile'])
cache_map.update_calc_status(subchash, query, dict(
curr_wait=sleeptime,
finished=sizes['finished'],
concsize=sizes['concsize'],
fullsize=sizes['fullsize'],
relconcsize=sizes['relconcsize'],
arf=None,
task_id=self._task_id))
tmp_cachefile = initial_args['cachefile'] + '.tmp'
conc.save(tmp_cachefile) # whole
os.rename(tmp_cachefile, initial_args['cachefile'])
sizes = self.get_cached_conc_sizes(corpus_obj, query, initial_args['cachefile'])
cache_map.update_calc_status(subchash, query, dict(
curr_wait=sleeptime,
finished=sizes['finished'],
concsize=sizes['concsize'],
fullsize=sizes['fullsize'],
relconcsize=sizes['relconcsize'],
arf=round(conc.compute_ARF(), 2) if not is_subcorpus(corpus_obj) else None,
task_id=self._task_id))
# update size in map file
cache_map.add_to_map(subchash, query, conc.size())
except Exception as e:
# Please note that there is no need to clean any mess (unfinished cached concordance etc.)
# here as this is performed by _get_cached_conc()
# function in case it detects a problem.
import traceback
logging.getLogger(__name__).error('Background calculation error: %s' % e)
logging.getLogger(__name__).error(''.join(traceback.format_exception(*sys.exc_info())))
if cache_map is not None:
cache_map.update_calc_status(
subchash, query, dict(
finished=True,
curr_wait=sleeptime,
error=e.message if getattr(e, 'message', None) else e.__class__.__name__))
def __init__(self, conf, ident):
super().__init__(ident)
self._conf = conf
fixed_corp = conf.get('corpus')
self._preset_corp = CorpusManager().get_corpus(fixed_corp) if fixed_corp else None
def __call__(self, initial_args, subc_dirs, corpus_name, subc_name,
subchash, query, samplesize):
"""
initial_args -- a dict(cachefile=..., already_running=...)
subc_dirs -- a list of directories where to look for subcorpora
corpus -- a corpus identifier
subc_name -- subcorpus name (should be None if not present)
subchash -- an identifier of current subcorpus (None if no subcorpus is in use)
query -- a tuple/list containing current query
samplesize -- row limit
"""
cache_map = None
try:
corpus_manager = CorpusManager(subcpath=subc_dirs)
corpus_obj = corpus_manager.get_Corpus(corpus_name,
subcname=subc_name)
cache_map = self._cache_factory.get_mapping(corpus_obj)
if not initial_args['already_running']:
# The conc object bellow is asynchronous; i.e. you obtain it immediately but it may
# not be ready yet (this is checked by the 'finished()' method).
conc = self.compute_conc(corpus_obj, query, samplesize)
sleeptime = 0.1
time.sleep(sleeptime)
conc.save(initial_args['cachefile'], False, True,
False) # partial
while not conc.finished():
# TODO it looks like append=True does not work with Manatee 2.121.1 properly
tmp_cachefile = initial_args['cachefile'] + '.tmp'
conc.save(tmp_cachefile, False, True, False)
os.rename(tmp_cachefile, initial_args['cachefile'])
time.sleep(sleeptime)
sleeptime += 0.1
sizes = self.get_cached_conc_sizes(
corpus_obj, query, initial_args['cachefile'])
cache_map.update_calc_status(
subchash,
query,
finished=sizes['finished'],
concsize=sizes['concsize'],
fullsize=sizes['fullsize'],
relconcsize=sizes['relconcsize'],
arf=None,
task_id=self._task_id)
tmp_cachefile = initial_args['cachefile'] + '.tmp'
conc.save(tmp_cachefile) # whole
os.rename(tmp_cachefile, initial_args['cachefile'])
sizes = self.get_cached_conc_sizes(corpus_obj, query,
initial_args['cachefile'])
cache_map.update_calc_status(
subchash,
query,
finished=sizes['finished'],
concsize=sizes['concsize'],
fullsize=sizes['fullsize'],
relconcsize=sizes['relconcsize'],
arf=round(conc.compute_ARF(), 2)
if not is_subcorpus(corpus_obj) else None,
task_id=self._task_id)
# update size in map file
cache_map.add_to_map(subchash, query, conc.size())
except Exception as e:
# Please note that there is no need to clean any mess (unfinished cached concordance etc.)
# here as this is performed by _get_cached_conc()
# function in case it detects a problem.
import traceback
logging.getLogger(__name__).error(
'Background calculation error: %s' % e)
logging.getLogger(__name__).error(''.join(
traceback.format_exception(*sys.exc_info())))
if cache_map is not None:
cache_map.update_calc_status(subchash,
query,
finished=True,
error=e)
def find_cached_conc_base(
corp: AbstractKCorpus, subchash: Optional[str], q: Tuple[str, ...],
minsize: int) -> Tuple[Optional[int], Union[PyConc, InitialConc]]:
"""
Load a concordance from cache starting from a complete operation q[:],
then trying q[:-1], q[:-2], q:[:-i] etc. A possible found concordance can be
used to skip calculation of already available operations q[:-i].
arguments:
minsize -- a minimum concordance size to return immediately (synchronously); please
note that unlike wait_for_conc here we accept also 0
returns:
a 2-tuple [an index within 'q' where to start with non-cached results], [a concordance instance]
"""
corpus_manager = CorpusManager(subcpath=[])
start_time = time.time()
cache_map = plugins.runtime.CONC_CACHE.instance.get_mapping(corp)
cache_map.refresh_map()
calc_status = cache_map.get_calc_status(subchash, q)
if calc_status:
if calc_status.error is None:
if calc_status.created - corp.corp_mtime < 0:
logging.getLogger(__name__).warning(
'Removed outdated cache file (older than corpus indices)')
cache_map.del_full_entry(subchash, q)
else:
logging.getLogger(__name__).warning(
'Removed failed calculation cache record (error: {0}'.format(
calc_status.error))
cache_map.del_full_entry(subchash, q)
raise calc_status.normalized_error
if _contains_shuffle_seq(q):
srch_from = 1
else:
srch_from = len(q)
conc = InitialConc(corp=corp)
ans = (0, conc)
# try to find the most complete cached operation
# (e.g. query + filter + sample)
for i in range(srch_from, 0, -1):
cache_path = cache_map.readable_cache_path(subchash, q[:i])
# now we know that someone already calculated the conc (but it might not be finished yet)
if cache_path:
try:
ready = wait_for_conc(cache_map=cache_map,
subchash=subchash,
q=q[:i],
minsize=minsize)
if not ready:
if minsize != 0:
cancel_conc_task(cache_map, subchash, q[:i])
logging.getLogger(__name__).warning(
'Removed unfinished concordance cache record due to exceeded time limit'
)
continue
_, finished = _check_result(cache_map=cache_map,
subchash=subchash,
q=q[:i],
minsize=minsize)
if finished:
mcorp = corp
for qq in reversed(
q[:i]): # find the right main corp, if aligned
if qq.startswith('x-'):
mcorp = corpus_manager.get_corpus(qq[2:])
break
conc = PyConc(mcorp, 'l', cache_path, orig_corp=corp)
except (ConcCalculationStatusException,
manatee.FileAccessError) as ex:
logging.getLogger(__name__).error(
f'Failed to use cached concordance for {q[:i]}: {ex}')
cancel_conc_task(cache_map, subchash, q[:i])
continue
ans = (i, conc)
break
logging.getLogger(__name__).debug(
f'find_cached_conc_base({corp.get_conffile()}, [{", ".join(q)}]), '
f'conc: {conc.__class__.__name__}, '
f'must calc ops from {i} to {len(q)}, '
f'time: {(time.time() - start_time):.4f}')
return ans